Profile Evaluation for CS / Statistics / Operations Research & School Recommendations

[carpeomnia]

Hey everyone! Hoping to get an idea of the strength of my application and chances of getting into some of the schools below for a PhD. Left school to work at a management consulting firm which I believe is a bit untraditional. Would also appreciate any school recommendations/adjustments to my current list, any thoughts welcome! Thanks

 

Undergrad Institution: Top 10 University in Canada
Major(s): Data Science
GPA: 3.96 (Last 4 Semesters/2 Years), 3.96 (Major), 3.89 (Cumulative)

Type of Student: Black International (Canadian) Male

GRE General Test: Taking summer 2022
 

Programs Applying: Computer Science (PhD), Statistics (PhD), Operation Research (PhD)

 

Research Experience:

• 2 first-author ACM conference papers (1 applied machine learning and has been cited, 1 data/text mining)
• 1 last-author conference paper (data/text mining; awarded Best Track Paper in Data Analytics and Big Data)
• 1 journal publication in geospatial statistics (submitted)
• Other research in applied machine learning and finance (no publication)
   

Awards/Honors/Recognitions: 

• Gold Medal (graduated with the highest GPA in Major, top of the class)
• Undergraduate Fulbright Fellowship

Letters of Recommendation: 

• One strong letter from an Associate Professor in Statistics & Management Science who I wrote the geospatial statistics paper with (not well-known in CS)
• One strong letter from an Assistant Professor in Data Science & Business Analytics who I published two papers with in data/text mining (not well-known in CS)
• One decent/strong letter from an Associate Professor in Economics & Statistics who I performed research with (~1yr together) but no publication
• One strong letter from a Partner at my management consulting firm (relevant for Operations Research programs)

Computer Science Courses: Intro CS I & CS II, Data Structures & Algorithms, Software Tools & Systems, Discrete Structures/Discrete Math, Analysis of Algorithms, Databases I, Data Science I
Math/Statistics Courses: Probability & Stats I & II, Statistical Programming, Calc I, Calc II, Intermediate Calc I, Intermediate Calc II, Linear Algebra I, Linear Algebra II, Numerical Analysis, ODEs, Modelling and Simulation, Regression, Generalized Linear Models, Advanced Statistical Computing, Statistical Learning

Any Miscellaneous Points that Might Help: Particularly interested in doing research within the field of Machine Learning (and potentially NLP), still figuring this out. Not particularly interested in CV or RL. Would have spent >1 year at a management consulting firm at the time of applying and >2 years by matriculation (a advantage/disadvantage?)

Applying to Where: In no particular order here,
CMU - PhD in Machine Learning
University of Washington - PhD in Computer Science
Columbia - PhD in Computer Science
MIT - PhD in EECS
Princeton - PhD in Computer Science
Cornell - PhD in Computer Science
NYU - PhD in Data Science
UIUC - PhD in Computer Science
UT Austin - PhD in Computer Science
UPenn - PhD in Computer Science
UC San Diego - PhD in Computer Science
UCLA- PhD in Computer Science
Georgia Tech - PhD in Machine Learning
UMichigan - PhD in Computer Science

CMU - PhD in Statistics
University of Washington - PhD in Statistics
Stanford - PhD in Statistics*
Cal Berkeley - PhD in Statistics
UPenn - PhD in Statistics
Yale - PhD in Statistics & Data Science
Stanford - PhD in Statistics
Cal Berkeley - PhD in Statistics
UPenn - PhD in Statistics
UMichigan - PhD in Statistics

CMU - PhD in Operations Research
MIT - PhD in Operations Research
Georgia Tech - PhD in Industrial and Systems Engineering
UMichigan - PhD in Industrial and Operations Engineering

Thanks again! 

Edited May 18, 2022 by carpeomnia